Occupant injury risk analysis at NASS/CDS database

Injury information for vehicle occupants from the body regions of the head, thorax, abdomen, and upper and lower extremities, due to the restraints and interior parts of the vehicle, were extracted from the 2009 ~ 2012 NASS/CDS database. For those cases with high occurrence frequency, a detailed and comprehensive data analysis was performed to find the relationship between the accident, occupant, vehicle, and injury data. A numerical frontal impact sled model with the Hybrid III dummy and the GHBMC human body model was constructed to simulate and identify those injury risks according to NASS/CDS. Among the 5,734 injuries to the aforementioned body regions from frontal crashes are, listed by frequency of occurrence, the lower extremity (27.8 %), upper extremity (21.3 %), thorax (15.1 %), face (10.9 %), spine (8.7 %), head (7.3 %), and abdomen (6.9 %). The main injury sources to the head were the windshield, side structure, and steering wheel. For the thorax and abdomen they were the seat belt and steering wheel. For the lower extremity it was the instrument panel. The main injury patterns for the head were the concussion and the contusion. For the thorax they were vessel laceration and lung contusion. For the abdomen they were laceration and contusion of the organs. For the lower extremity they were bone fracture and ligament rupture. The steering wheel and seat positions were main factors affecting head and thorax injury risks. From the sled impact simulation, high injury risks of the head and thorax were assessed respectively at conditions of steering column tilt down and rear most seat position, which correlated well with the findings from the NASS/CDS data analysis.     

Optimal Preview Control of a Two-dof Vehicle Model Using Stochastic Optimal Control Theory

An optimal preview control algorithm is applied to a two degree of freedom(dof) vehicle model travelling with constant velocity on a randomly profiled road. The road roughness is modelled as a homogeneous random process being the output of a linear first order filter to white noise. The input from the road irregularity is assumed to be measured at some distance in front of the vehicle and this measured infonnation is utilized by the active controller to prepare the system for the ensuing input. The preview control algorithm is obtained by minimizing a quadratic performance index and by describing the average behaviour of the system by the covariance matrix of the vehicle response state vector. Results are presented for full state feedback and significant improvements in sprung mass acceleration, suspension working space and road holding are observed.     

Discrete Adaptive Active Suspension for Hardware Implementation

This paper presents a discrete adaptive control approach for an active suspension. The study involves formulation of an active suspension as a digital controller problem involving the time delays. A nonlinear time varying (NTV), single input single output (SISO) suspension model is considered for the analysis. A discrete model reference adaptive control (DMRAC) approach with recursive least square (RLS) estimation is used to form the controller. The controller is designed to maintain the static equilibrium irrespective of dynamic load variations as a disturbance force on the model. Simulation results for deterministic and stochastic inputs are presented to substantiate the approach. Results indicate good performance of adaptive controller even for large dynamic variations of the model and has the potential for a successful hardware implementation.     

Fuel consumption of fuel cell hybrid vehicles considering battery SOC differences

Fuel cell hybrid vehicles (FCHVs) have become one of the most promising candidates for future transportation due to current energy supply problem and environmental problem. Fuel economy is an important factor in FCHVs. In order to properly evaluate the fuel economy of an FCHV, the initial battery state of charge (SOC) and the final battery SOC have to be identical so that the effect of the battery energy usage on the fuel economy is neglected. In the simulation or in the real driving, however, the final battery SOC is usually different from the initial battery SOC, and the final battery SOC often depends on the power management strategy. To consider the difference between the two battery SOC values, the concept of equivalent fuel consumption is presented by two methods. One is based on the relationship between delta SOC and delta fuel consumption, and the other is based on the optimal control theory. Two rule-based power management strategies for an FCHV are presented, and for each strategy, the fuel economy is evaluated based on the two methods. The characteristics of the two methods are discussed and compared, and the superior one is selected based on the comparison.     

Prediction of the dimensional deformation of the addendum and dedendum after the warm shrink fitting process using a correction coefficient

The warm shrink fitting process is generally used to assemble automobile transmission parts (shafts/gears). However, this process causes a deformation in the addendum and dedendum of the gear depending on the fitting interference and gear profile, and this deformation causes additional noise and vibration between the gears. To address these problems, the warm shrink fitting process is analyzed by considering the error in the dimensional deformation of the addendum and dedendum found when comparing the results of a theoretical analysis and finite element analysis (FEA). A correction coefficient that reduces this error is derived through an analysis of the difference in the cross-sectional area between the shapes used for the theoretical analysis and that of the actual gear, and a closed-form equation to predict the dimensional deformation of the addendum and dedendum is proposed. The FEA method is proposed to analyze the thermal-structural-thermal coupled field analysis of the warm shrink fitting process (heating-fitting-cooling process). To verify the closed-form equation using the correction coefficient, measurements are made of actual helical gears used in automobile transmissions. The results are in good agreement with those given by the closed-form equation.     

Improvement of long-term lives of rubber gaskets of polyacrylate (ACM) by employing carboxyl cure sites

Rubber gaskets are used widely in many industries. An evaluation of the material properties and an accurate lifetime prediction of rubber are very important in the design process to ensure the durability and reliability of rubber components. The properties of rubber-like materials are sensitive to ambient conditions, such as temperature, environment and mechanical load. Moreover, the initial properties of rubber gaskets must be sustained under working conditions to maintain its sealing function. To perform tests within a reasonable time, the highly accelerated life test (HALT) is generally used to predict the long-term lifetime of rubber materials. Polyacrylate (ACM) with chlorine cure sites is generally used for engine head gaskets. An ACM with carboxyl cure sites was developed to improve the lifetime of the gaskets. A four-parameter method representing the recovery behavior of the gaskets was published recently, and two revised methods for obtaining the recovery were proposed. The mean squared errors (MSEs) of the regression methods and experimental data were compared. The life of a gasket for the target recovery (60%) of a compressed gasket was calculated somewhat differently depending on the selected regression model to predict a considerably different long-term life. The parameters in the regression models were obtained using the successive zooming genetic algorithm (SZGA), and the lives of ACM with a carboxyl cure site and ACM with a chlorine cure site were compared.     

Analysis of the shifting behavior of a novel clutchless geared smart transmission

Conventional geared transmissions use some kinds of clutches to control the power flow from an internal combustion engine to the driveline while shifting gears. However, the shifting performance is seriously affected by the clutch engagement and an unavoidable drop in the torque may occur when the clutch is disconnected. Moreover, wear of the clutch, the need for hydraulic equipment, and the load limit may together aggravate the limits of the clutch system. For this reason, as a novel transmission without a clutch, the clutchless geared smart transmission (henceforth CGST) is proposed by our research team. The CGST controls the power flow in a multiple-input gear-train by controlling the electric motor attached to the planetary gear system. However, no CGST has been realized in an actual vehicle thus far, and the performance has been predicted only theoretically. In this research, we analyzed the achievable performance based on a developed CGST dynamic model with a typical CGST structure. In addition, a CGST gear-shifting algorithm is proposed for use with the dynamic model. From the simulation results, the CGST does not show an abrupt drop in its torque or oscillation while shifting gears due to the absence of a discontinuous power flow. The developed dynamic model can serve as a performance reference for the CGST. Moreover, it can be used as a simulation tool for developing a gear-shifting control logic scheme.     

Preview suspension control for a full tracked vehicle

In this study, preview control algorithms for the active and semi-active suspension systems of a full tracked vehicle (FTV) are designed based on a 3-D.O.F model and evaluated. The main issue of this study is to make the ride comfort characteristics of a fast moving tracked vehicle better to keep an operator’s driving capability. Since road wheels almost trace the profiles of the road surface as long as the track doesn’t depart from the ground, the preview information can be obtained by measuring only the absolute position or velocity of the first road wheel. Simulation results show that the performance of the sky-hook suspension system almost follows that of full state feedback suspension system and the on-off semi-active system carries out remarkable performance with the combination of 12 on-off semi-active suspension units. The results simulated with 1^st and 2^nd weighting sets mean that the suspension system combined with the soft type of inner suspension and hard type of outer suspension can carry out better ride comfort characteristics than that with identical suspensions. The full tracked vehicle (FTV) system is uncontrollable and the system is split into controllable and uncontrollable subspace using singular value decomposition transformation. Frequency response curves to four types of inputs, such as heaving, pitching, rolling, and warping inputs, also demonstrate the merits of preview control in ride comfort. All the frequency characteristic responses confirm the continuous time results.     

Durability prediction for automobile aluminum front subframe using nonlinear models in virtual test simulations

This research work presents fatigue life evaluation techniques for an automotive vehicle aluminum front subframe using virtual test simulation technology with nonlinear suspension components model. The technology was used for improving the accuracy of the polynomial model used in conventional analysis. The proposed nonlinear suspension components models were developed using direct approach. The effects of the nonlinear elements on the prediction of the fatigue life were also analyzed. Actual aluminum front subframe was tested using half-car road test simulator to verify the accuracy of the models. It was found that the proposed nonlinear models yield more accurate results than conventional polynomial models. The proposed virtual test simulation technology with nonlinear suspension components model can be used to predict fatigue life for vehicle chassis structures more accurately.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).